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The Handbooks in Economics series continues to provide the various branches of economics with handbooks which are definitive reference sources, suitable for use by professional researchers, advanced graduate students, or by those seeking a teaching supplement. The Handbook of Economic Growth, edited by Philippe Aghion and Steven Durlauf, with an introduction by Robert Solow, features in-depth, authoritative survey articles by the leading economists working on growth theory

The Handbooks in Economics series continues to provide the various branches of economics with handbooks which are definitive reference sources, suitable for use by professional researchers, advanced graduate students, or by those seeking a teaching supplement. The Handbook of Economic Growth, edited by Philippe Aghion and Steven Durlauf, with an introduction by Robert Solow, features in-depth, authoritative survey articles by the leading economists working on growth theory

This paper presents a framework for understanding the limits that exist in optimal policy design in dynamic contexts. We consider the design of policies in the context of dynamic linear models. Fundamental design limits exist for policy rules in such environments in the sense that any policy rule embodies tradeoffs between the magnitudes of different frequency‐specific components of the variance. Hence policies that are effective in eliminating low frequency variance components of a state variable can only do so at the cost of exacerbating high frequency variance components, and vice versa. Examples of the implications of such tradeoffs are considered.

This article questions current empirical practice in the study of growth. It argues that much of the modern empirical growth literature is based on assumptions about regressors, residuals, and parameters that are implausible from the perspective of both economic theory and the historical experiences of the countries under study. Many of these problems, it argues, are forms of violations of an exchangeability assumption that implicitly underlies standard growth exercises. The article shows that these implausible assumptions can be relaxed by allowing for uncertainty in model specification. Model uncertainty consists of two types: theory uncertainty, which relates to which growth determinants should be included in a model; and heterogeneity uncertainty, which relates to which observations in a data set constitute draw from the same statistical model. The article proposes ways to account for both theory and heterogeneity uncertainty. Finally, using an explicit decision-theoretic framework, the authors describe how one can engage in policy-relevant empirical analysis.

Although Tobin 1955 was one of the founding papers of the neoclassical one-sector growth model with smooth substitution between capital and labor, James Tobin's contributions to long-run growth theory throughout his career stood apart from other neoclassical growth models because of his emphasis on portfolio substitution between money and capital as a possible source of the non-neutrality of money even in the long run. This paper examines Tobin's contributions to growth theory over more than four decades and the relationship of his work to the evolution of modern growth economics.

This paper examines Lionel Robbins' critical attitude towards formal empirical work from the standpoint of modern econometrics. It argues that his attitude towards empirical work rested on indefensible assumptions and that he failed to realise that the role he saw for empirical work undermined his belief in the primacy of economic theory. This matters because Robbins' attitudes are echoed in modern economics, best exemplified by the calibration methodology of Kydland and Prescott, which is vulnerable to similar criticisms.